A majority of business leaders understand, at least in theory, the importance of data analytics in relation to performance and growth. In fact, a recent global survey of Chief Financial Officers and Chief Information Officers found more than 99 percent of organizations believe data analytics is somewhat important to their businesses.
But despite seeing the value in analytics, 96 percent of respondents say their organizations are still leaving benefits on the table. Why? Many companies are struggling to analyze stored data, make decisions related to their data strategy, and integrate new technology into their existing models.
Grabbing the data analytics bull by the horns requires more than just deploying certain tools; there needs to be buy-in and true leadership from C-level executives to drive the data strategy.
Here are some essentials C-levels need to understand about data analytics.
Analytics Is More Than a Technology-Only Challenge
Investing in the right tools is an important aspect of data analytics, of course. But it’s not only about technology. Creating a data-driven culture to support this technology is another key piece of the puzzle — one many organization are finding challenging as they try to ramp up their data strategies.
What can executives do to foster a more data-driven company culture from the top down? Lead by example. Rather than paying lip service to the importance of data analytics, use the findings in decision-making. Use all-hands meetings and meetings with employees as an opportunity to tie data analytics into performance goals. Set expectations for employees across the organization to do the same.
The takeaway here is executives must do more than authorize the financial investment in data analytics tools. They should use them, talk about them, and ask questions about them, too. This involvement will help forge a culture uniformly steeped in data.
The Benefits of Moving Away from Data Silos
Data was traditionally considered the domain of specialists — tightly guarded by the IT team, which acted as a gatekeeper between data and the rest of the organization. Today it’s entirely possible to democratize data by making it accessible widely to employees and partners while still maintaining strong central governance over it for cybersecurity reasons.
As TechCrunch notes, easy access to high-quality data from a central source empowers employees to make data-driven decisions on the spot, but “this doesn’t mean handing over the keys to all the data to all the staff.”
Here’s how this could look in action.
A customer service representative at a telecommunications company is able to access data about product performance during phone calls with frustrated customers. This allows them to offer better recommendations and solutions in real time. But does this person suddenly have access to all top-secret, high-level performance data? No, because administrators are able to set permissions to keep data secure.
There Is a Cost to “Just Getting By” with Existing Tech
There are costs associated with forgoing advanced analytics tools. Research from Gartner has estimated employee adoption rates to be around 30 percent. User friendliness plays a significant role in boosting adoption rates, as does accessibility of tools and shareability of findings.
Choosing to “just get by” for the time being with legacy tech may save you an up-front investment in more advanced systems, but there will be costs associated — like low adoption and missed opportunities to capitalize on stored data during decision-making processes.
The C-Suite Should Play a Role in Solving the Talent Gap
There’s a high demand for data talent, which can lead to organizations experiencing a talent gap. The C-suite can and should play a role in solving this issue by clearly defining roles then strategically hiring a team of professionals with complementary skillsets. In addition to making hiring decisions, executives also have a hand in fostering a data-centric company culture in which employees get the training and tools they need to meet their daily data needs — freeing up data specialists from getting too bogged down by reporting backlogs.
Above all, C-level leaders need to understand how much influence they have over the success of an organization’s data analytics strategy.